Sociological Content Analysis Research Paper Starter

Sociological Content Analysis

In the social sciences, it is often impossible to gather data through direct observation or experimental manipulation. Frequently, however, usable data can be collected for analysis in such situations through content analysis. This systematic analysis examines the content of artifacts of human society and parses them into explicit, distinct categories. Content analysis enables researchers to relatively quickly and easily reduce large amounts of information into quantifiable data that can be meaningfully analyzed. Two basic approaches are used for developing coding schemes for content analysis: The a priori method and the emergent method. However, no matter which method is used, it is important that the resultant coding scheme have both high inter-rater reliability and content validity in order for the data to be of use for research or theory building. When properly used, content analysis can be an invaluable tool for social science researchers analyzing social and cultural phenomena.

Sociological Content Analysis

Overview

Social science research is concerned with collecting data about a broad array of factors that influence society and the behavior of individuals within society. However, it is not always possible to gather data by directly observing human behavior. In some situations it is not possible to directly measure a dependent variable at all because individuals may feel reluctant or unable to articulate certain feelings or emotions due to their personal sensitivity (e.g., abuse), political incorrectness (e.g., prejudice), or inability to express the feeling in words. This situation is compounded when trying to gain and analyze data about larger segments of society rather than about individuals. Sometimes, a researcher may be interested in measuring and analyzing a broad concept for all of society. It is virtually impossible to directly gather information about the opinions and beliefs of society in general. Further, such concepts tend to be nebulous, and frequently cannot be operationally defined in terms of behaviors. Therefore, more unobtrusive measures must be used. For situations such as these, it is often helpful for the researcher to examine available data in artifacts of human thought and behavior and to extrapolate back to the underlying construct.

Secondary Data Used for Content Analysis

There is a wide range of secondary data that are available to support researchers who desire to study data in human artifacts. Diaries and personal correspondence can be analyzed to determine a subject's state of mind or emotions. Newspaper or periodical articles can be analyzed to determine the state of mind of a sample of individuals on a given subject (e.g., attitudes towards immigration, reaction to local issues). Television shows, movies, music lyrics, or video games can be examined to determine other cultural trends (e.g., attitudes towards violence, acceptance of teenage sex). Information is mined through such sources using a technique called content analysis: The systematic analysis of the content (as opposed to the format) of artifacts of human society (e.g., newspaper, periodicals, diaries) into explicit, distinct categories. The results of content analysis can be used in both quantitative and qualitative research paradigms.

Benefits of Content Analysis

There are a number of reasons use content analysis.

• First, this technique enables researchers to systematically review and analyze large volumes of data in a way that could not be done (or not be done easily) by other methods.

• Second, content analysis allows researchers to extract data from historical artifacts when it is no longer possible to gain information from the subjects themselves (e.g., historical data).

• Third, content analysis can help researchers determine and articulate the focus of individuals, groups, institutions, or society in general. Content analysis is often used for identifying and analyzing trends and patterns in documents. This technique provides researchers with a basis to monitor trends and shifts in public opinion.

There are a number of advantages to using content analysis. First, content analysis has little to no effect on the subject's behavior. Content analysis is performed after the fact on artifacts of human behavior. Therefore, it does not influence that behavior because the artifact of human behavior has already been produced. In addition, content analysis enables researchers to gather data and information on aspects of human behavior within society that could not otherwise be gathered because subjects are unwilling or unable to directly share their attitudes or feelings on a topic.

Disadvantages of Content Analysis

Content analysis is not without its disadvantages. First, since content analysis is typically based on mass communication, it is limited to data that can be disseminated through such sources. In addition, content analysis is subject to the limitations of other data collection techniques that use human raters. The rating criteria for content analysis need to be operationally well-defined a priori to increase the consistency of ratings. However, even when this is done, the criteria used to operationally define constructs may not be universally accepted and, therefore, cannot be replicated or extrapolated. Further, since content analysis is based on subjective criteria, it is relatively easy for experimenter error to influence the results of the analysis. Experimenter error occurs when the influence of the expectations, beliefs, prejudices, or other attitudes of the researcher affect the data collection process and the subsequent interpretation of the results. For example, when performing a content analysis of violence in television shows, a rater who believes that there is a high incidence of violence in children's television shows is likely to find more violent contents in the shows analyzed than is a rater who does not believe this to be true. Such lack of inter-rater reliability means that the content analysis is not valid and, therefore, not usable for the study.

Preparations for Content Analysis

Before beginning a content analysis, several questions must first be answered. As in any research paradigm, the first step that must be taken is to define and bound the problem. For example, if one were interested in the correlation of violence in the media to violence in real life, one might first develop a hypothesis that stated that an increase in violence in television shows watched by adolescents over the past decade has led to an increase in violence committed by adolescents in real life. Before data could be collected to test this hypothesis, however, one would first need to operationally define the terms "television shows," "violence," "media," and "real life." One would need to determine which television shows were most watched by adolescents not only currently, but also a decade ago. The researcher would also need to further define the population of adolescents of interest for the study. For example, the researcher might be only interested in changes in violent acts by inner-city adolescents. Based on this focus, the researcher would then draw sample only from inner-city youth. However, the results of the study could not be extrapolated to include all adolescents. The researcher would also have to operationally define the term "violence." To do this, the researcher could develop a series of non-overlapping criteria to define violence (e.g., harassment, abuse, assault, battery, murder). These terms would need to be operationally defined not only for violence in the real world, but also for rating incidents of violence in television programs. For example, a rating code might include specific categories such as reference to a violent act, showing the aftermath of a violent act, or showing the violent act itself. Once these parameters were defined, the researcher would next train raters on how to rate these criteria in television shows.

Importance of Reliability

It is important that any coding scheme used in content analysis be both reliable and valid. Reliability is the consistency with which the coding scheme measures whatever it is measuring; validity is the degree to which the coding scheme measures what it is intended to measure. A coding scheme cannot be valid unless it is reliable. For content analysis, the type of reliability of most interest is inter-rater reliability. This is the consistency with which different raters obtain similar results using the same data collection criteria. Frequently, this is done by having the raters who will review the same material rate a sample of the data. Their...